math-engine 0.2.1

A fast and secure mathematical expression evaluator.

Math Engine 0.2.1

A fast, safe, configurable expression parser and calculator for Python

math_engine is a powerful expression evaluation library designed for developers who need a safe, configurable, and extendable alternative to Python’s built-in eval() or other ad-hoc parsers. It provides a complete pipeline:

• Tokenizer
• AST (Abstract Syntax Tree) parser
• Evaluator (numeric + equation solver)
• Formatter and type-safe output system
• Support for decimal, integer, binary, octal, hexadecimal
• Custom variables
• Scientific functions
• Strict error codes for reliable debugging and automated testing

Version 0.2.1 adds extensive non-decimal number support (hex, binary, octal), prefix-based type casting, improved settings management, and expanded error reporting.

This library is ideal for:

• Developers building calculators, interpreters, scripting engines
• Students learning compilers, math parsing, and ASTs
• Security-sensitive applications where eval() is not acceptable
• Anyone who needs equation solving, custom formats, and strict errors

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Features

Core Features

• Full AST-based expression parsing

• Safe evaluation (no execution of Python code)

• Decimal, Integer, Float, Boolean, Binary, Octal, Hexadecimal

• Custom variables

• Linear equation solving (x + 3 = 7)

• Scientific functions: sin, cos, tan, log, sqrt, π, e^

• Automatic format correction (correct_output_format)

• Strong error handling with unique codes

• Settings system with presets

• Optional strict modes:

  • only_hex
  • only_binary
  • only_octal

Non-Decimal Support (0.2.1)

• Read binary 0b1101
• Read octal 0o755
• Read hexadecimal 0xFF
• Convert results into binary/hex/octal format
• Enforce only-hex/only-binary/only-octal mode
• Prefix parsing (hex:, bin:, int:, str: ...)

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Installation

pip install math-engine

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Quick Start

Basic Evaluation

import math_engine

math_engine.evaluate("2 + 2")
# Decimal('4')

Different Output Formats

math_engine.evaluate("hex: 255")
# '0xff'

math_engine.evaluate("binary: 13")
# '0b1101'

math_engine.evaluate("octal: 64")
# '0o100'

Automatic Format Correction

math_engine.load_preset({"correct_output_format": True})
math_engine.evaluate("boolean: 3+3=6")
# True

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Prefix System (Casting Syntax)

math_engine supports a powerful prefix-based casting system:

Prefix	Meaning	Example
dec:	Decimal	dec: 3/2 → 1.50
int:	Integer	int: 10/3 → error if non-integer
float:	Float	float: 1/3
bool:	Boolean	bool: 3 = 3
hex:	Hexadecimal	hex: 15
bin:	Binary	bin: 5
oct:	Octal	oct: 64
str:	String	str: 3+3 → "6"

Example:

math_engine.evaluate("hex: 3 + 3")
# '0x6'

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Variables

vars = {
    "A": 10,
    "B": 5
}

math_engine.evaluate("A + B", custom_variables=vars)
# Decimal('15')

Variables must be single characters (to enforce safety and keep parsing simple).

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Scientific Functions

math_engine.evaluate("sin(30)")
math_engine.evaluate("cos(90)")
math_engine.evaluate("log(100,10)")
math_engine.evaluate("√(16)")
math_engine.evaluate("pi * 2")

All functions are processed by the internal ScientificEngine.

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Linear Equation Solver

math_engine.evaluate("x + 3 = 10")
# Decimal('7')

Invalid or nonlinear equations produce errors with codes like:

• 3005 – Non-linear equation
• 3002 – Multiple variables
• 3022 – One side empty

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Non-Decimal Numbers (Binary, Octal, Hex)

math_engine.evaluate("0xFF + 3")
# Decimal('258')

math_engine.evaluate("0b1010 * 3")
# Decimal('30')

Force-only-hex mode

settings = math_engine.load_all_settings()
settings["only_hex"] = True
math_engine.load_preset(settings)

math_engine.evaluate("FF + 3")
# Decimal('258')

Input validation ensures safety.

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Settings System

You may load presets:

preset = {
    "decimal_places": 2,
    "use_degrees": false,
    "allow_augmented_assignment": true,
    "fractions": false,
    "allow_non_decimal": true,
    "debug": false,
    "correct_output_format": true,
    "default_output_format": "decimal:",
    "only_hex": false,
    "only_binary": false,
    "only_octal": false
}

math_engine.load_preset(preset)

Or modify single settings:

math_engine.save_setting("decimal_places", 10)

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Error Handling

Every error is a custom exception with:

• Human-readable message
• Machine-readable error code
• Position (if applicable)
• The original expression

Example:

try:
    math_engine.evaluate("1/0")
except math_engine.error.CalculationError as e:
    print(e.code)  # 3003

Example Error Codes

Code	Meaning
3003	Division by zero
3034	Empty input
3036	Multiple = signs
3032	Multiple-character variable
8000	Conversion to int failed
8006	Output conversion error

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Testing and Reliability

math_engine is designed with testing in mind:

• Full error-code consistency
• Strict syntax rules
• Unit-test friendly behavior
• No reliance on Python’s runtime execution

You can easily test error codes:

import pytest
from math_engine import error as E

def test_div_zero():
    with pytest.raises(E.CalculationError) as exc:
        math_engine.evaluate("1/0")
    assert exc.value.code == "3003"

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Performance

• No use of Python eval()
• Predictable performance through AST evaluation
• Optimized tokenization
• Fast conversion of non-decimal numbers

Future updates focus on:

• Expression caching
• Compiler-like optimizations
• Faster scientific evaluation

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Use Cases

Calculator Applications

Build full scientific calculators, both GUI and command line.

Education

Great for learning about lexers, parsers, ASTs, and expression evaluation.

Embedded Scripting

Safe math evaluation inside larger apps.

Security-sensitive Input

Rejects arbitrary Python code and ensures controlled evaluation.

Data Processing

Conversion between hex/bin/decimal is easy and reliable.

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Roadmap (Future Versions)

• Non-decimal output formatting upgrades
• Strict type-matching modes
• Function overloading
• Bitwise operators (&, |, ^, <<, >>)
• Memory/register system
• Speed optimization via caching
• User-defined functions
• Expression pre-compilation
• Better debugging output

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License

MIT License

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Contributing

Contributions are welcome. Feel free to submit issues or PRs on GitHub:

https://github.com/JanTeske06/math_engine

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